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Getting started

Before starting

Before starting, you will need:

Steps

To setup the ARLAS Exploration Stack, you can either start the required docker containers or start individually the processes on the command line (one rest server and one http server).

Tip

For simplicity, we recommend using the docker containers for running the ARLAS Exploration Stack.

Steps

To setup the ARLAS Exploration Stack, you will need to

  • configure & start ARLAS Server
  • register your Elasticsearch index as an ARLAS Collection
  • and finally configure & start ARLAS WUI

Using docker

Step 1: ARLAS Server

docker run -d \
   -p 9999:9999 \
   -e "ARLAS_ELASTIC_CLUSTER=myelasticsearchclustername" \
   -e "ARLAS_ELASTIC_NODES=elasticsearchhostname:9300" \
   gisaia/arlas-server:latest

Important

ARLAS_ELASTIC_HOST and ARLAS_ELASTIC_PORT no longer exist starting from v10.6.0. They're replaced by ARLAS_ELASTIC_NODES.

For further configuration details, see the ARLAS Server configuration page.

Step 2: Registering data

Register your Elasticsearch index within ARLAS Exploration:

curl -X PUT \
  --header 'Content-Type: application/json;charset=utf-8' \
  --header 'Accept: application/json' \
  'http://localhost:9999/arlas/collections/mycollection' \
  --data @collection.json

where collection.json contains:

{
   "index_name": "my.index.name",
   "type_name": "type.within.my.index",
   "id_path": "path.to.the.id",
   "geometry_path": "path.to.the.geometry",
   "centroid_path": "path.to.the.centroid",
   "timestamp_path": "path.to.the.timestamp",
   "include_fields": "*"
}

See the tutorial and the collection api documentation for further help on how to manage your ARLAS Collections. Read the collection model documentation to understand the fields within your index required for becoming an ARLAS Collection.

Step 3: ARLAS WUI

Setup a configuration file (config.json) for ARLAS-WUI and then start it by providing the HTTP URL of the configuration file:

docker run -d \
   -p 80:80 \
   -e ARLAS_WUI_CONFIGURATION_URL=http://myhostname/path/to/config/file.json  \
   -e ARLAS_WUI_MAP_CONFIGURATION_URL=http://myhostname/path/to/config/file.map.json  \
   -e ARLAS_WUI_ABOUT_CONFIGURATION_URL=http://myhostname/path/to/config/file.md\
   -e ARLAS_WUI_I18N_EN_URL=http://myhostname/path/to/english/language/file_en.json  \
   -e ARLAS_WUI_I18N_FR_URL=http://myhostname/path/to/french/language/file_fr.json  \
   gisaia/arlas-wui:latest

Note

ARLAS_WUI_MAP_CONFIGURATION_URL, ARLAS_WUI_ABOUT_CONFIGURATION_URL, ARLAS_WUI_I18N_EN_URL and ARLAS_WUI_I18N_FR_URL are optional.

Now, ARLAS WUI is up and running.

Optional : ARLAS-tagger

You can use ARLAS-tagger for building sophisticated data sets.

you will need:

  • a running Elasticsearch cluster (6.X)
  • with an index (your indexed data) having an identifier, a timestamp, a geometry and a centroid and registered in ARLAS-Exploration as a Collection with ARLAS-server
  • a running Kafka node
  • a machine with Docker for running ARLAS-tagger.
docker run -d \
   -p 9998:9998 \
   -e "ARLAS_ELASTIC_CLUSTER=myelasticsearchclustername" \
   -e "ARLAS_ELASTIC_NODES=elasticsearchhostname:9300" \
   -e "KAFKA_BROKERS=kafkahostname:9092" \
   gisaia/arlas-tagger:latest